themis: Extra Recipes Steps for Dealing with Unbalanced Data

A dataset with an uneven number of cases in each class is said to be unbalanced. Many models produce a subpar performance on unbalanced datasets. A dataset can be balanced by increasing the number of minority cases using SMOTE 2011 <arXiv:1106.1813>, BorderlineSMOTE 2005 <doi:10.1007/11538059_91> and ADASYN 2008 <https://ieeexplore.ieee.org/document/4633969>. Or by decreasing the number of majority cases using NearMiss 2003 <https://www.site.uottawa.ca/~nat/Workshop2003/jzhang.pdf> or Tomek link removal 1976 <https://ieeexplore.ieee.org/document/4309452>.

Package details

AuthorEmil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>)
MaintainerEmil Hvitfeldt <emilhhvitfeldt@gmail.com>
LicenseMIT + file LICENSE
Version0.1.4
URL https://github.com/tidymodels/themis https://themis.tidymodels.org
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("themis")

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themis documentation built on June 13, 2021, 1:06 a.m.